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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…Therefore, in this study a new optimized variant of machine learning algorithms is presented. …”
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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle
Published 2023“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications
Published 2023Article -
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…Genetic Algorithms are very efficient at exploring the entire search space; however, they are relatively poor at finding the precise local optimal solution in the region at which the algorithm converges. …”
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…Using a number of candidate detectors from an improved Apriori Algorithm with Particle Swarm Optimization, the true positive rate of detecting malicious code is maximized, while the false positive rate of wrongful detection is minimized. …”
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Particle swarm optimization for neural network learning enhancement
Published 2006“…To overcome this problem, Genetic Algorithm (GA) has been used to determine optimal value for BP parameters such as learning rate and momentum rate and also for weight optimization. …”
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Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms
Published 2025“…This study delves into the exploration of different algorithms, including Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Firefly Algorithm (FA), Invasive Weed Optimization (IWO), Teaching Learning-Based Optimization (TLBO), and Harmony Search (HS). …”
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling
Published 2025“…However, limited attention has been given to CHFS when considering holistic cost models using efficient algorithms. This paper presents a novel Greedy-Assisted Teaching-Learning-Based Optimization (GTLBO) algorithm for CHFS. …”
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Intelligent energy systems using the barnacles mating optimizer and evolutionary mating algorithm: Foundations, methods, and applications
Published 2026“…Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm: Foundations, Methods, and Applications reveals the potential of innovative optimization algorithms to support sustainability in modern energy systems. …”
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Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…This thesis presents a new approach to optimize the performance of a dual beam optical scanning system in terms of its scanning combinations and speed, using Genetic Algorithm (GA). …”
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The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement
Published 2025“…In the past few decades, there have been multiple algorithms proposed for the purpose of solving optimization problems including Machine Learning (ML) applications. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023“…Normally, a user takes several months of learning in order to become highly productive in using a specific object-oriented application framework. …”
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Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization
Published 2023“…This paper introduces a new variant of the metaheuristic algorithm based on the naked mole rat (NMR) algorithm, called the Q-learning naked mole rat algorithm (QL-NMR), for substitution box construction and optimization. …”
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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms
Published 2015“…To further augment the ARTMAP's pattern classification ability, multiple ARTMAPs were optimized via genetic algorithm and assembled into a classifier ensemble. …”
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